Enterprise systems store outcomes, not reasoning. Context graphs capture decision context, enabling AI agents and turning systems of record into systems of reasoning.
Using AI in quality assurance is now essential to staying competitive, but teams still need to stay grounded and involve people to balance the hype with real results.
The reason your staged rollouts still cascade, and the drain-before-advance pattern that fixes it, is inspired by one of history's greatest mathematicians.
Kafka feeds the stream, Spark tracks progress via checkpoints, and Delta's transaction log ensures every event lands exactly once, even across failures and restarts.
Agentic AI transforms retail order sourcing by using real-time demand, weather, and supply data to reduce markdowns, optimize inventory, and boost margins.
AI coding agents can refactor a microservice in seconds. So why are developers still spending half their day waiting to find out if their code actually works?
A practical playbook for deploying generative AI at scale, covering governance, security, risk controls, and best practices for safe, compliant production use.
A custom framework testing Oracle 26ai’s ability to convert natural language into SQL using the 22 TPC-H benchmark. With no prompt engineering, it achieves high accuracy.
Securely connect to a MongoDB DocumentDB replica set in Kubernetes using mongosh with credentials retrieved dynamically from Kubernetes secrets for direct access.
Learn the Moment Indexing Pattern to build a Video Evidence Layer using OCR and ASR that provides verifiable, timecoded answers for knowledge management.
Many AI tools fail in production not because of model quality, but due to architectural decisions around retries, cost control, observability, and multi-tenant safety.
AI fails silently in safety-critical systems — classify failures and enforce safety with voting, OOD detection, and a Simplex-style deterministic override.
CORE
